Evidence map›Paper›PMID 33198484›Full record

ArticleCirculation. Arrhythmia and electrophysiology2020

Personalized Digital-Heart Technology for Ventricular Tachycardia Ablation Targeting in Hearts With Infiltrating Adiposity.

Eric Sung, Adityo Prakosa, Konstantinos N Aronis, Shijie Zhou, Stefan L Zimmerman, Harikrishna Tandri, Saman Nazarian, Ronald D Berger, Jonathan Chrispin, Natalia A Trayanova

Open access · bronzeAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Circulation. Arrhythmia and electrophysiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
4.2field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
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  4. Computer-aided characterization of the arrhythmogenic substrate after myocardial infarction.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026
    Review
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  8. Reply to: Stochastic virtual heart model predictions.Nature cardiovascular research · 2025
    Article
  9. Observational
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  11. Left atrial intramyocardial fat at pulmonary vein reconnection sites during atrial fibrillation redo ablation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Article
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  19. Digital twins in medicine.Nature computational science · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Eric SungDepartment of Biomedical Engineering (E.S., A.P., S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.
Adityo PrakosaDepartment of Biomedical Engineering (E.S., A.P., S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.
Konstantinos N AronisAlliance for Cardiovascular Diagnostic and Treatment Innovation (E.S., A.P., K.N.A., S.Z., S.L.Z., H.T., R.D.B., J.C., N.A.T.), Johns Hopkins University, Baltimore, MD.
Shijie ZhouDepartment of Biomedical Engineering (E.S., A.P., S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.
Stefan L ZimmermanAlliance for Cardiovascular Diagnostic and Treatment Innovation (E.S., A.P., K.N.A., S.Z., S.L.Z., H.T., R.D.B., J.C., N.A.T.), Johns Hopkins University, Baltimore, MD.
Harikrishna TandriAlliance for Cardiovascular Diagnostic and Treatment Innovation (E.S., A.P., K.N.A., S.Z., S.L.Z., H.T., R.D.B., J.C., N.A.T.), Johns Hopkins University, Baltimore, MD.
Saman NazarianDivision of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.N.).
Ronald D BergerAlliance for Cardiovascular Diagnostic and Treatment Innovation (E.S., A.P., K.N.A., S.Z., S.L.Z., H.T., R.D.B., J.C., N.A.T.), Johns Hopkins University, Baltimore, MD.
Jonathan ChrispinAlliance for Cardiovascular Diagnostic and Treatment Innovation (E.S., A.P., K.N.A., S.Z., S.L.Z., H.T., R.D.B., J.C., N.A.T.), Johns Hopkins University, Baltimore, MD.
Natalia A TrayanovaDepartment of Biomedical Engineering (E.S., A.P., S.Z., N.A.T.), Johns Hopkins University, Baltimore, MD.
Anna Needs Neuroblastoma Answers · USJohns Hopkins University · USUniversity of Pennsylvania · US

Funding

Infarct-related Ventricular Tachycardia Mechanisms: From Micro to ClinicalR01HL142496 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2019 to 2022
$3.1M
Exploration of Arrhythmogenic Triggers and Substrates in Heart FailureR01HL126802 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI EFIMOV, IGOR R, GORELIK, JULIA · 2016 to 2019
$2.8M
Implications of Intra-Myocardial Fat Deposition upon Propensity for Malignant ArrhythmiaR01HL142893 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI NAZARIAN, SAMAN, TRAYANOVA, NATALIA A. · 2018 to 2021
$2.5M
NHLBI NIH HHS R01 HL126802NHLBI NIH HHS R01 HL142496NHLBI NIH HHS R01 HL142893
6 · The paper itself

Abstract

backgroundInfiltrating adipose tissue (inFAT) is a newly recognized proarrhythmic substrate for postinfarct ventricular tachycardias (VT) identifiable on contrast-enhanced computed tomography. This study presents novel digital-heart technology that incorporates inFAT from contrast-enhanced computed tomography to noninvasively predict VT ablation targets and assesses the capability of the technology by comparing its predictions with VT ablation procedure data from patients with ischemic cardiomyopathy.

methodsDigital-heart models reflecting patient-specific inFAT distributions were reconstructed from contrast-enhanced computed tomography. The digital-heart identification of fat-based ablation targeting (DIFAT) technology evaluated the rapid-pacing-induced VTs in each personalized inFAT-based substrate. DIFAT targets that render the inFAT substrate noninducible to VT, including VTs that arise postablation, were determined. DIFAT predictions were compared with corresponding clinical ablations to assess the capabilities of the technology.

resultsDIFAT was developed and applied retrospectively to 29 ischemic cardiomyopathy patients with contrast-enhanced computed tomography. DIFAT ablation volumes were significantly less than the estimated clinical ablation volumes (1.87±0.35 versus 7.05±0.88 cm

conclusionsDIFAT is a novel digital-heart technology for individualized VT ablation guidance designed to eliminate VT inducibility following initial ablation. DIFAT predictions colocalized well with clinical ablation locations but provided significantly smaller lesions. DIFAT also predicted VTs targeted in redo procedures years later. As DIFAT uses widely accessible computed tomography, its integration into clinical workflows may augment therapeutic precision and reduce redo procedures.

Indexed as

AdiposityCatheter AblationPatient-Specific ModelingSurgery, Computer-AssistedTomography, X-Ray ComputedAgedFeasibility StudiesFemaleHeart VentriclesHumansMaleMiddle AgedPredictive Value of TestsRegistriesRetrospective StudiesTachycardia, Ventricularadiposityarrhythmiacatheter ablationhearttachycardiatomography

Identifiers

PMID33198484
PMCPMC7738410
OpenAlexW3106219733

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.